Bottom Line:
A significant minority of individuals (n=21) could not be scanned successfully due to their large size.Multiple regression analysis showed that gender, puberty status, LM and FM were associated with the magnitude of the bias.In the longitudinal study of 51 individuals, the mean bias in change in fat or LM did not differ significantly from zero (FM: Delta=-0.02, P=0.9; LM: Delta=0.04, P=0.8), however limits of agreement were wide (FM: +/-3.2 kg; LM: +/-3.0 kg).

Background: Body composition is increasingly measured in pediatric obese patients. Although dual-energy X-ray absorptiometry (DXA) is widely available, and is precise, its accuracy for body composition assessment in obese children remains untested.

Objective: We aimed to evaluate DXA against the four-component (4C) model in obese children and adolescents in both cross-sectional and longitudinal contexts.

Design: Body composition was measured by DXA (Lunar Prodigy) and the 4C model in 174 obese individuals aged 5-21 years, of whom 66 had a second measurement within 1.4 years. The Bland-Altman method was used to assess agreement between techniques for baseline body composition and change therein.

Results: A significant minority of individuals (n=21) could not be scanned successfully due to their large size. At baseline, in 153 individuals with complete data, DXA significantly overestimated fat mass (FM; Delta=0.9, s.d. 2.1 kg, P<0.0001) and underestimated lean mass (LM; Delta=-1.0, s.d. 2.1 kg, P<0.0001). Multiple regression analysis showed that gender, puberty status, LM and FM were associated with the magnitude of the bias. In the longitudinal study of 51 individuals, the mean bias in change in fat or LM did not differ significantly from zero (FM: Delta=-0.02, P=0.9; LM: Delta=0.04, P=0.8), however limits of agreement were wide (FM: +/-3.2 kg; LM: +/-3.0 kg). The proportion of variance in the reference values explained by DXA was 76% for change in FM and 43% for change in LM.

Conclusions: There are limitations to the accuracy of DXA using Lunar Prodigy for assessing body composition or changes therein in obese children. The causes of differential bias include variability in the magnitude of tissue masses, and stage of pubertal development. Further work is required to evaluate this scenario for other DXA models and manufacturers.

Figure 1: Mean bias in fat mass and lean mass, calculated as the DXA value – 4C value, according to pubertal stage. The error bars represent the limitations of agreement, calculated as twice the standard deviation of the mean bias.

Mentions:
The bias in weight estimated by DXA was 0.21 (SD 0.57) kg, p<0.0001. Table 3 presents the Bland-Altman statistics for the evaluations of DXA. Compared to the 4C model, DXA significantly over-estimated FM in the entire sample by 0.9 kg. This finding was replicated in each sex when considered separately. The limits of agreements of this bias were ±4.2 kg, but were greater in girls (±4.7 kg) than in boys (±3.1 kg). DXA similarly under-estimated LM by 1.0 kg in the entire sample, with limits of agreement in individuals of ±4.2 kg. Variable bias in weight between individuals accounts for the inconsistency in mean biases for FM and LM. When the sexes were considered separately, the bias was greater in females (−1.2 kg) than males (0.67 kg), though not significantly so. The magnitude of the bias differed significantly by pubertal stage, with both greater bias, and wider limits of agreement, in those of more advanced pubertal stage (Figure 1). The bias was greater in those receiving Metformin (FM: 2.2 ± 3.0 kg versus 0.7 ±1.9 kg, p=0.065; LM: −2.1 ±2.7 kg versus −0.9 ±2.0 kg, p=0.032). However, multiple regression analysis showed that when age and BMI SDS were added to the model, those receiving Metformin did not have significantly greater bias in FM or LM, indicating it was their above-average BMI and age that accounted for the greater bias.

Figure 1: Mean bias in fat mass and lean mass, calculated as the DXA value – 4C value, according to pubertal stage. The error bars represent the limitations of agreement, calculated as twice the standard deviation of the mean bias.

Mentions:
The bias in weight estimated by DXA was 0.21 (SD 0.57) kg, p<0.0001. Table 3 presents the Bland-Altman statistics for the evaluations of DXA. Compared to the 4C model, DXA significantly over-estimated FM in the entire sample by 0.9 kg. This finding was replicated in each sex when considered separately. The limits of agreements of this bias were ±4.2 kg, but were greater in girls (±4.7 kg) than in boys (±3.1 kg). DXA similarly under-estimated LM by 1.0 kg in the entire sample, with limits of agreement in individuals of ±4.2 kg. Variable bias in weight between individuals accounts for the inconsistency in mean biases for FM and LM. When the sexes were considered separately, the bias was greater in females (−1.2 kg) than males (0.67 kg), though not significantly so. The magnitude of the bias differed significantly by pubertal stage, with both greater bias, and wider limits of agreement, in those of more advanced pubertal stage (Figure 1). The bias was greater in those receiving Metformin (FM: 2.2 ± 3.0 kg versus 0.7 ±1.9 kg, p=0.065; LM: −2.1 ±2.7 kg versus −0.9 ±2.0 kg, p=0.032). However, multiple regression analysis showed that when age and BMI SDS were added to the model, those receiving Metformin did not have significantly greater bias in FM or LM, indicating it was their above-average BMI and age that accounted for the greater bias.

Bottom Line:
A significant minority of individuals (n=21) could not be scanned successfully due to their large size.Multiple regression analysis showed that gender, puberty status, LM and FM were associated with the magnitude of the bias.In the longitudinal study of 51 individuals, the mean bias in change in fat or LM did not differ significantly from zero (FM: Delta=-0.02, P=0.9; LM: Delta=0.04, P=0.8), however limits of agreement were wide (FM: +/-3.2 kg; LM: +/-3.0 kg).

Background: Body composition is increasingly measured in pediatric obese patients. Although dual-energy X-ray absorptiometry (DXA) is widely available, and is precise, its accuracy for body composition assessment in obese children remains untested.

Objective: We aimed to evaluate DXA against the four-component (4C) model in obese children and adolescents in both cross-sectional and longitudinal contexts.

Design: Body composition was measured by DXA (Lunar Prodigy) and the 4C model in 174 obese individuals aged 5-21 years, of whom 66 had a second measurement within 1.4 years. The Bland-Altman method was used to assess agreement between techniques for baseline body composition and change therein.

Results: A significant minority of individuals (n=21) could not be scanned successfully due to their large size. At baseline, in 153 individuals with complete data, DXA significantly overestimated fat mass (FM; Delta=0.9, s.d. 2.1 kg, P<0.0001) and underestimated lean mass (LM; Delta=-1.0, s.d. 2.1 kg, P<0.0001). Multiple regression analysis showed that gender, puberty status, LM and FM were associated with the magnitude of the bias. In the longitudinal study of 51 individuals, the mean bias in change in fat or LM did not differ significantly from zero (FM: Delta=-0.02, P=0.9; LM: Delta=0.04, P=0.8), however limits of agreement were wide (FM: +/-3.2 kg; LM: +/-3.0 kg). The proportion of variance in the reference values explained by DXA was 76% for change in FM and 43% for change in LM.

Conclusions: There are limitations to the accuracy of DXA using Lunar Prodigy for assessing body composition or changes therein in obese children. The causes of differential bias include variability in the magnitude of tissue masses, and stage of pubertal development. Further work is required to evaluate this scenario for other DXA models and manufacturers.